首页|尺度适应重力波拖曳方案在高分辨率数值预报中的应用研究

尺度适应重力波拖曳方案在高分辨率数值预报中的应用研究

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随着数值模式分辨率越来越高,在复杂地形区域仅考虑高层重力波拖曳作用和地形阻塞作用具有局限性,WRFv4.3模式中新型重力波拖曳方案在原有大尺度重力波拖曳和地形阻塞作用基础上新加入了边界层小尺度重力波拖曳作用,且对湍流地形拖曳作用增加了描述,从而可以达到尺度适应.为了验证新的重力波拖曳方案的效果,本文基于华北区域3 km对流可分辨模式开展了 2021年冬季重力波拖曳参数化方案应用试验,对比分析了三组试验方案:不开启重力波拖曳、原有的仅考虑大尺度重力波拖曳和阻塞作用的方案以及新型的尺度适应方案的模拟结果.试验结果表明:原有重力波拖曳方案仅考虑重力波拖曳和大尺度地形阻塞,在3 km模式中对复杂地形附近整层风场影响较大,但是正效果有限;新型尺度适应重力波拖曳方案在3 km分辨率模式中大尺度重力波拖曳和阻塞拖曳作用为0,仅由边界层内小尺度重力波拖曳和湍流地形拖曳起作用,能够达到尺度适应效果;由于高层重力波拖曳为0,开启新型重力波拖曳会降低低空尤其是边界层内风场预报正偏差,对高空风场无影响;对模拟区域的统计检验结果表明,新型重力波拖曳方案可以有效减少地形复杂区域近地面风场预报的误差,但对温度等其它要素的改善有限.
Application of a Scale-Aware Gravity Wave Drag Scheme in High-Resolution Numerical Weather Prediction
As the resolution of numerical prediction systems increases,the subgrid-scale orographic gravity wave drag(GWD)and low-level blocking parameterization become less suitable.To address this issue,WRFv4.3 has introduced two additional orographic drag suites:small-scale GWD and turbulent orographic form drag,thus evolving into a scale-aware scheme.To evaluate the performance of this high-resolution model,application tests were conducted over North China.Three schemes were designed:a model with GWD shut down,a model with the original GWD activated,and a model with the new scale-aware GWD activated.The results reveal that the original GWD,which contains only subgrid-scale orographic GWD and low-level blocking without varying resolution,significantly affects wind at all levels in the model;however,the effect is not always positive.In contrast,the scale-aware GWD scheme minimizes the aforementioned factors to zero while maintaining small-scale GWD and turbulent orographic drag in the 3-km model.Therefore,the drag force exists only in the planetary boundary layer,and the low-level wind can be effectively improved.Statistical results show that the scale-aware GWD scheme can significantly decrease the positive bias and root mean square error of near-surface wind forecasts.However,for other variables,the improvement was not significant.

Gravity wave dragScale-awareNumerical weather predictionParameterization schemeStrong wind prediction

张涵斌、史永强、卢冰、夏宇、吴志鹏

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北京城市气象研究院,北京 100089

克拉玛依市气象局,新疆克拉玛依 934000

重庆市气象台,重庆 401147

重力波拖曳 尺度适应 数值天气预报 参数化方案 强风预报

国家重点研发计划资助项目中国南方电网有限责任公司科技项目

2021YFC30009012021YFC3000901

2024

大气科学
中国科学院大气物理研究所

大气科学

CSTPCD北大核心
影响因子:2.11
ISSN:1006-9895
年,卷(期):2024.48(2)
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